一种基于改进遗传算法的自适应区域生长法研究  

A New Adaptive Region Growing Method Based on Improved Genetic Algorithms

作　　者：吴涛[1] 毕笃彦[1] 

机构地区：[1]空军工程大学工程学院,陕西西安710038

出　　处：《微电子学与计算机》2008年第4期90-92,97,共4页Microelectronics & Computer

摘　　要：区域生长法是图像分割的一种常用的方法,但该方法中种子点的选取仍需人为地判定,从而影响了分割效果.因此将遗传算法引入模糊C-均值聚类方法,不仅克服了模糊C-均值聚类的局部性和对初始聚类中心的敏感性,同时也实现了图像种子点数目和位置自动选择和确定.实验结果表明这种方法是可行和有效的,它扩大了遗传算法和模糊C-均值聚类的应用领域.Region growing algorithm is a common image segmentation method, but in this method seeds can only be judged by human experience. Genetic algorithm is induced into fuzzy clustering to solve the locality and sensitiveness of the initial condition of fuzzy C - means clustering, simultaneously carry out that the number and location of seeds can be chose automatically. The experiment shows that the method is feasible and efficient, and it widens the application of genetic algorithm and fuzzy theory.

关 键 词：图像分割 区域生长 种子点 模糊C-均值聚类 遗传算法 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]